Hello S4-class boffins,
How bad of an idea it is to inherit from a S4Vectors::DataFrame / DFrame S4
class to impose additional constraints on it? I'm writing a light-weight
wrapper around the ToppGene web API (github
com/ImmuSystems-Lab/toppgene/blob/main/R/categories.R) [1] and while it's
functional, it currently only runs JSON web queries using default values. To
pass non-default values, each category queried needs to have associated
parameters within some boundaries. While it's intuitive for a Biconductor user
to see and manipulate DataFrames containing the parameters, the trouble I'm
seeing is that validObject() is of course not automagically run on the
dispatched S4Vectors setters and I don't know how to inject validObject() into
the process without rewriting / repeating a lot of the S4Vectors method
implementation internals; callNextMethod() does not seem like it would work?
Currently, the only time validObject() is called is when invoking the
constructor, CategoriesDataFrame() and because code is worth a thousand words,
see below the "---" line for what I mean.
Pariksheet
[1] Yes, I'm trying to avoid the GitHub URL from being mangled into illegible
horrors by removing the protocol prefix and the dot before the domain, so
you'll have to add at least the latter back in to visit the GitHub page.
---
> devtools::load_all()
[...]
> cats <- CategoriesDataFrame()
> cats
ToppGene CategoriesDataFrame with 19 enabled categories
PValue MinGenes MaxGenes MaxResults Correction
Enabled
Coexpression 0.05 2 1500 50 FDR
TRUE
CoexpressionAtlas 0.05 2 1500 50 FDR
TRUE
Computational 0.05 2 1500 50 FDR
TRUE
Cytoband 0.05 2 1500 50 FDR
TRUE
Disease 0.05 2 1500 50 FDR
TRUE
Domain 0.05 2 1500 50 FDR
TRUE
Drug 0.05 2 1500 50 FDR
TRUE
GeneFamily 0.05 2 1500 50 FDR
TRUE
GeneOntologyBiologicalProcess 0.05 2 1500 50 FDR
TRUE
GeneOntologyCellularComponent 0.05 2 1500 50 FDR
TRUE
GeneOntologyMolecularFunction 0.05 2 1500 50 FDR
TRUE
HumanPheno 0.05 2 1500 50 FDR
TRUE
Interaction 0.05 2 1500 50 FDR
TRUE
MicroRNA 0.05 2 1500 50 FDR
TRUE
MousePheno 0.05 2 1500 50 FDR
TRUE
Pathway 0.05 2 1500 50 FDR
TRUE
Pubmed 0.05 2 1500 50 FDR
TRUE
TFBS 0.05 2 1500 50 FDR
TRUE
ToppCell 0.05 2 1500 50 FDR
TRUE
------------------------------
Values allowed by ToppGene are:
PValue: [0, 1] <numeric>
MinGenes: [1, 5000] <integer>
MaxGenes: [2, 5000] <integer>
MaxResults: [1, 5000] <integer>
Correction: {None, FDR, Bonferroni} <character>
## This next line should not complete without an error! But it does.
> cats[, "PValue"] <- 2
## Explicitly calling validObject() will point out the problem post-hoc,
## but not prevent the above assignment.
> validObject(cats)
Error in validObject(cats) :
invalid class “CategoriesDataFrame” object: column PValue must contain values
<= 1
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